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Generative AI
Cloud
Testing
Artificial intelligence
Security
May 20, 2025
With governments seeking to boost efficiency, improve public services, and address complex societal challenges, public sector organizations have high expectations for AI. According to the new report, within the next 2-3 years, 39% of public sector organizations aim to evaluate the feasibility of agentic AI, 45% intend to explore pilot programs, and 6% plan to scale their existing agentic AI initiatives. Attitudes towards agentic AI adoption are mostly consistent across segments, levels of government, and organizational sizes. The report finds that nearly two-thirds (64%) of organizations have progressed to pilots and scaled deployments, or are exploring Gen AI, with this number rising to 82% in defense agencies, 75% in healthcare, and 70% in security.
“With rising citizen demands and stretched resources, public sector organizations recognize the ways in which AI can help them do more with less. However, the ability to deploy Gen AI and agentic AI depends on having rock-solid data foundations,” said Marc Reinhardt, Public Sector Global Industry Leader at Capgemini. “Looking ahead, governments can be more agile and effective as AI augments the work of government employees to source information, conduct policy analysis, make decisions, and answer citizen queries. However, to reach this future, governments need to focus on building the right data infrastructure and governance frameworks.”
Despite ambitions to embrace and scale AI use, public sector executives cite data security issues (79%) and limited trust in AI-generated outputs (74%) as primary barriers to widespread adoption. In the EU, organizations report a significant gap in confidence when it comes to complying with the EU AI Act[1], with less than four in ten (36%) prepared to meet these requirements.
To progress their Gen AI adoption, public sector organizations require better data mastery, with the public sector showing limited progress in key areas of data management and utilization since 2020. The report finds that only 12% of organizations consider themselves very mature in activating data, while 7% report being very mature in nurturing data and AI-related skills. Only a fifth (21%) of public sector organizations surveyed have the required data to train and fine-tune AI models, including Gen AI models.
Data sharing is vital for AI adoption as it boosts the volume and diversity of data to enhance AI model performance and optimize decision making. But data sharing initiatives are further complicated by concerns about data, cloud, and AI sovereignty. Despite all public sector organizations surveyed either having or planning to have data sharing initiatives, they are not yet mature; most organizations (65%) worldwide are still in the planning or pilot stages.
Governments are increasingly recognizing the critical role of harnessing data in the public sector, and this is reflected in the growing prominence of Chief Data Officers (CDO) and Chief AI Officers (CAIO). As many as 64% of public sector organizations already have a CDO, while 24% plan to appoint one, showing a willingness to invest in dedicated leadership for data-driven governance. Furthermore, the increasing strategic value of AI has resulted in over a quarter (27%) of public sector organizations appointing a Chief AI Officer, over a quarter (27%) already having one and 41% planning to introduce this new C-level role.
In December 2024 and January 2025, the Capgemini Research Institute conducted a survey of executives from 350 public sector organizations with two respondents from each organization – one from the IT/data function and one from a line of business (LOB). These executives represented organizations across six public sector segments: public administration, tax and customs, welfare, defense, security, and healthcare. They operated at various levels of government, including national, state, local, and international, and were located in countries across North America, Europe, APAC, and the Middle East.
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